Profiting from innovation strategy: the role of it initiatives and R&D.

ABSTRACT

Company-wide pursuit of innovation is a pivotal condition of survival in the new competitive environment where this pursuit exists not only in the forms of goods and services, but also in processes, systems, and business practices (Shervani and Zerrillo, 1997). During the past two decades, rapid changes in information technology (IT) has enabled businesses to go through major transformations. Many new IT initiatives, including web-enhanced service, IT-enabled mega mergers, supply chain integration and distributed databases, were implemented. To support these initiatives, most companies have substantially increased IT spending (Hitt et. al., 2002). Empirical studies exploring the association between profitability and IT, however, have resulted in inconclusive, and often contradictory findings. At the same time, new technologies and techniques resulting from R&D investments have been seen as new differentiation factors (Lee, 2003). In order to shed additional light on the relationship between IT investments, R&D spending and firm performance, the importance of innovation strategy as an explanatory factor in understanding the relationship between IT and profitability needs to be examined further. The question of whether IT innovators spend more on R&D (including IT expenditures) and thus are more profitable than non-innovators is explored. Data was collected from over 100 firms in the U.S. chemicals industry. The statistical analyses suggest that chemical companies that invest heavily in information technologies are larger than their non-IT counterparts. The two groups of companies, IT innovators and non-IT innovators, differ in their strategic focus. The larger, IT intensive companies invest more heavily in information technologies while their smaller competitors appear to have the strategy of investing more intensively in R&D. Neither strategy seems to be more profitable than the other.

1. INTRODUCTION

How effective are IT investments in improving business performance and value? The linkage between IT and performance can be better understood by examining the impact of IT on productivity and profitability separately. Early evidence from macro-level productivity measures suggested that the computerization of businesses did not lead to improved productivity (Brynjolfsson & Hitt, 1998). This was contradictory to the thought that IT as a revolutionary innovation would bring new and better results for companies, including higher productivity. Because of inconsistent results, the term "productivity paradox" was coined and was used with various explanations such as measurement errors in inputs and outputs, aggregation of data, lags in learning and adjustment, redistribution of profits and mismanagement of IT. However, more recent firm-level analyses utilizing bigger sample sizes found that information technology had a positive effect on the efficiency of a firm (Brynjolfsson & Hitt, 1998; McKinsley and Company, 2002). These studies have led to questioning the validity of the productivity paradox.

On the relationship between IT and firm profitability, some empirical studies suggest that association between profitability and IT is either weak, or nonexistent because of the measures used for profitability (e.g., Brynjolfsson, 1998; Hickman and Raia , 2002; Rai, Patnayakuni and Patnayakuni, 1997). Other studies support increased profitability and financial performance (Hitt and Brynjolfsson, 1996; Rai, Patnayakuni and Patnayakuni, 1997) being attributable to IT. However, other financial measures such as the connection between return on investment and IT are either not significant (Rai, Patnayakuni and Patnayakuni, 1997) or negative (Brynjolfsson, 1998; Hickman and Raia , 2002). The findings are supported by some observations and anecdotal evidence. Still some firms are more successful than others in realizing the value of their IT investments. In some cases, inept IT deployment has led, in part, to poor financial performance and even bankruptcy, e.g., the bankruptcy of FoxMeyer Health attributed to a flawed implementation of SAP software.

1.1 Information Technology and Corporate Strategy

As reviewed above, IT investments do not always lead to higher profitability (Rai, Patnayakuni and Patnayakuni, 1997). Often, deployment of IT necessitates redesigning business processes and shifting strategic focus, causing profitability to vanish from IT investments. Research suggests that the strategic choices made by a firm are the intervening factors which, in conjunction with investment activities such as IT investments, can contribute to higher profitability. The key word here is alignment, which has been validated by various historical studies. In fourteen annual surveys of top management conducted by CSC (CSC, 2001), alignment of information systems and corporate goals ranked very high among the twenty critical information system issues--in most years ranking as the most critical.

Despite the emerging conclusions connecting profitability, IT and certain corporate strategies, very little research focuses on corporate strategy as a mitigating variable linking IT and profitability. A study by Gurubaxani and Wang (1999) confirmed that IT alone did not enhance profits, return on assets, or return on equity, but in combination with vertical disintegration and diversification strategies it did.

1.2 Perspectives of Innovation as a Strategy

Innovation is the process by which businesses improve their competitiveness and profitability by creating and/or adopting relevant new products and ideas. Innovation strategy has been recognized as an effective response to competitive forces. The objective of innovation strategy is to identify those promising opportunities for the firm to pursue. Usually, the driver of successful innovation decisions is the firm's new product strategy. This is formulated by aligning the firm's distinctive competencies with the market opportunities that provide good customer value. Innovations result in the development of new products and services, new features in existing products and services, and new ways to produce or sell them. The scope of innovation can be quite varied. Activities ranging form automation of order taking to developing hydrogen-powered automobiles are broadly considered innovations.

To clarify the relationship between innovation, corporate strategic scope and organizational capabilities, four different perspectives of innovations ranging from incremental innovation to innovations leading to drastic change have been offered (Hickman & Raia, 2002). These four perspectives can be grouped into 1) innovations that improve core businesses and exploit strategic advantages, and 2) innovations that develop new capabilities and lead to revolutionary change. Many, if not most, IT initiatives can be considered as innovations belonging to the first group that improve core businesses. Enterprise resource planning, supply chain management, customer relationship management, data warehouses and data mining, and upgrades to communications infrastructure are popular IT initiatives implemented by medium to large enterprises. A distinguishing feature of these initiatives is that they provide opportunities to improve organizational processes, better coordinate value chains, provide up-to-date information to improve decision making, and increase customer satisfaction. However, not all IT initiatives are considered revolutionary and thus do not result in industry-wide changes in business practices.

1.3 Innovators

Innovators are the companies that engage in achieving revolutionary changes in technologies, techniques, know-how, processes, product offering, and production efficiency. Christensen (1997) pointed to the importance of the market/technology match in achieving innovation success with discontinuous technologies. Her study indicated that discontinuous technologies require various initiatives to be directed to market niches where the traditional technology does not serve well. Guan and Ma (2003) studied innovative capability from seven interrelated dimensions: learning, research and development (R&D), manufacturing, marketing, organizational, resource allocating, and strategy planning. Chesbrough (2003) suggested the abandonment of "closed innovation" that embraces a strategy of vertical integration and exclusive control because this isolationism stifles innovation. Information now flows cheaply and instantaneously over the Web and even though people today are more widely dispersed geographically, they are actually more closely connected. Thus companies must adapt to "open innovation" by accessing and exploiting outside knowledge while liberating their own internal expertise for others' use. Operationally, Industrial Research Institute in Washington includes the following as key indicators of successful innovators: communicating the importance of research projects, setting demanding innovation objectives, and focusing innovation efforts on areas where knowledge gaps exist and potential is promising.

1.4 IT innovations and R&D

Innovation in industries has lead to strategic divergence (Lee, 2003). Economists have long believed that firms in an industry should be alike in all economically important dimensions except for their size because competition will eventually eliminate intra-industry heterogeneity. Although research has tried to show empirically that firms using different strategies can coexist in an industry, there is still little agreement about the why such intra-industry heterogeneity exits and what may have caused such (Dranove et al. 1998). One answer to this question lies in the origins and evolution of strategic divergence within a particular industry (Peteraf and Shanley 1997) whereby innovation has not only lead to intra-industry heterogeneity, but has maintained or even further intensified such heterogeneity.

IT innovations and R&D can be viewed as different response strategies to competitive forces. IT innovations lead to improvements in internal processes, coordination, and decision making, while R&D leads to changes in products, services, and markets served by a firm. Considerable studies have been conducted on the issues of R&D Some research suggests that strategic R&D success factors include embedment into the scientific system, development of core competencies, securing appropriability, choosing appropriate organizational structures and processes (Brockhoff, 2003). Yet, still little is known about how these two, IT innovation strategy and R&D strategy relate to each other. Do firms expend effort to pursue both IT innovations and R&D simultaneously and with some focus, or do they choose one innovation strategy over the other? Is there a preferred sequence to pursue these strategies? Are there financial performance differences for firms pursuing these two different strategies?

2. RESEARCH QUESTIONS

It can be argued that innovators seek opportunities to improve efficiencies in existing operations with IT innovations as well as prepare for the future with R&D efforts simultaneously. However, resources available for innovations are limited. Resource constraints may force a company to choose between improving existing operations (IT focused innovations), and actively seeking new products, services and markets (R&D focused innovations). This paper sheds light on the above issues and measures the financial consequences of their chosen strategies. The following hypotheses have been developed based on the previous literature review and discussion:

H1: Companies that invest in IT innovation intensively also invest in R&D intensively, and vice versa.

The past research on R&D suggests that there is a marked relationship between firm size and R&D. For example the strength of the relationship that exists between inventive output of a firm (as measured by number of patents) and size of the firm (as measured by sales or R&D employees) has been investigated. This study will test if these expectations hold true for IT innovation.

H2: A positive relationship exists between firm size and the level of IT innovations.

It would be reasonable to expect that those companies that pursue an IT innovation strategy would be more efficient and hence more profitable. This leads to:

H3: Those companies that pursue an IT innovation strategy are more profitable than those that do not.

3. RESEARCH METHODOLOGY

To test the above hypotheses the Chemical Industry was chosen. Past studies have found that there are substantial differences among different industries in the level of IT investments (Shin, 2001) and the results obtained due to IT (McKinsley and Company, 2002; Stiroh, 2001). Similarly, literature shows that different industries invest in R&D at very different levels and even use R&D intensity as the definition of industry technology level. To observe variation in R&D intensity levels and IT innovation, high-tech and low-tech industries are avoided. Information Week's Annual Survey of IT Innovators in the chemical industry served as the initial dataset in the study. There were 59 different companies listed from 1996 to 2001. A company was considered to be an IT innovator if it showed up on any of the six annual lists included in the data.

Structural and financial data for similar companies were obtained from Standard and Poor's Compustat. The resulting dataset included publicly traded companies of which 36 of the original 59 companies coming from 26 distinct primary SIC codes were included. The total dataset included 651 companies of which 615 companies were not classified as IT innovators. Data concerning each company in the sample included: primary SIC code, annual revenues, assets, R&D expenses, R&D intensity (R&D expenses divided by annual revenues), ROA, and ROE. These data were collected for the years 1994 to 2002 (from two years preceding the IT innovation listing to the ending date). The dates allowed for testing the companies for differences before their listing and throughout the tested period. This approach allowed for identification of significant changes that may have occurred due to the companies' involvement or lack of involvement in IT initiatives.

The data from the two distinct groups were compared using t-tests on company size, R&D investment size, R&D intensity and profitability for three distinct time periods, 1994-1996, 1997-1999, and 2000-2002. These time periods can be thought of as pre-IT innovation, IT innovation and post-IT innovation. The tests were used to determine if significant differences existed between IT innovators and non-IT Innovators with respect to the attributes mentioned. The multiple time frames allowed the influence of innovation to be judged over time.

4. RESULTS

The results of the statistical tests are listed below in tables 1, 2 and 3. Note that IT innovators are larger companies than their non-IT innovator counterparts in all time periods. In each of the time periods, this was statistically significant with a p-value of less than 1%. The R&D intensities of the two groups were also compared and found to be statistically different with the smaller, non-IT innovators investing much more intensely in R&D across all time periods. These results show that H3 is rejected while H2 is not rejected if considering IT investments or absolute R&D investments. In fact, absolute R&D expenses of the groups were tested and the larger, IT innovators were found to spend greater amounts than their smaller counterparts at a statistically significant level in all time periods. However, the R&D intensity was much larger for the smaller, non IT intensive companies. This suggests that H2 should be rejected if considering the intensity of R&D investments. Finally, profitability of the two groups was compared and no statistical differences were found in the later two time periods, thus H1 was rejected. However, the profitability measures did show statistical differences in the first time period with those companies that later invested intensively in IT being more profitable. This profitability advantage disappeared in the last two time periods.

5. DISCUSSION AND CONCLUSIONS

Companies in the chemical industry appear to be choosing proven strategies over time with respect to their foci on IT innovation versus R&D intensity. Neither strategy seems to be inherently more advantageous than the other. However, it appears that companies are selecting strategies that yield similar economic advantages as demonstrated by the statistical tests of the profitability ratios. Notice that the larger, more complex companies focus their innovation strategy on IT investments which are consistent with previous research. In contrast, the smaller, less complex companies focus their innovation strategy on R&D investments. These patterns have continued through all time periods under investigation. It is interesting to notice that smaller companies in the study have benefited by greater R&D intensity (a strategy focus usually associated with longer-term returns) and smaller IT innovations (a shorter-term horizon).

Larger organizations in the study show that they have benefited by having lesser R&D intensity and greater IT innovation for the nine year period. As companies create competitive strategies they must be consistent with market requirements if they are to be successful. It is reasonable to expect that larger firms will avail themselves of IT usage to a greater degree than smaller firms because of the costs and the need for using this technology, i.e., the increased complexity of size. One of the interesting results of this study is that greater use of IT by larger firms brings financial success; however, the smaller companies with less IT usage also show good financial returns. This result will question "what is good for GM is good for the country". Clearly, additional studies are needed to validate the argument.

This study limited itself to R&D and IT innovations of chemical industry firms. It revealed that greater R&D and greater IT innovation were not simultaneously pursued strategies by the sampled firms. Factors such as previous investments, previous returns, new technologies, and other developments from specific technology investments could be influential factors. The study however adds to the understanding that IT innovations alone do not increase success even for firms in the same industry. This study also supports the literature and shows why findings in these studies often differ. Although IT innovation is not a high priority for smaller firms in this study they should benefit from its deployment. Studies involving investment versus return over time will help determine the resources needed to realize benefits. These studies could show investments needed for successful returns and possibly encourage smaller firms to be more IT innovative. Studies involving other business segments are needed. Issues such as these serve to further explain the value and role of investments in IT innovations.

TABLE 1: PRE IMPLEMENTATION YEARS: 1994, 1995 AND 1996

Dataset                Comparison of means             Conclusion *

Assets           [[bar.Assets].sub.ITIC] =
                 [[bar.Assets].NITIC]               ITIC have more
                                                    assets than NITIC
Revenues         [[bar.Revenues].sub.ITIC] =
                 [[bar.Revenues].sub.NITIC]         ITIC have more
                                                    revenues than
                                                    NITIC.
R&D              [[bar.R & D].sub.ITIC] =
                 [[bar.R & D].sub.NITIC]            ITIC spend more
                                                    absolute dollars
                                                    on R&D than NITIC
R&D intensity    [[bar.R&Dintensity].sub.ITIC] =
                 [[bar.R&Dintensity].sub.NITIC]     NITIC are more R&D
                                                    intensive than
                                                    ITIC.
ROA              [[bar.ROA].sub.ITIC] =
                 [[bar.ROA].sub.NITIC]              ITIC have greater
                                                    ROA than NITIC
ROE              [[bar.ROE].sub.ITIC] =
                 [[bar.ROE].sub.ITIC]               ITIC have greater
                                                    ROE than NITIC

Dataset          p-value

Assets            .000
Revenues          .000
R&D               .000
R&D intensity     .026
ROA               .000
ROE               .002

* ITIC refers to Information Technology Innovative Companies
NITIC refers to Companies that are not Innovators of Information
Technology

TABLE 2: IMPLEMENTATION YEARS: 1997, 1998 AND 1999

Dataset                Comparison of means            Conclusion *

Assets           [[bar.Assets].sub.ITIC] =
                 [[bar.Assets].sub.NITIC]           ITIC have more
                                                    assets than NITIC
Revenues         [[bar.Revenues].sub.ITIC] =
                 [[bar.Revenues].sub.NITIC]         ITIC have more
                                                    revenues than
                                                    NITIC.
R&D              [[bar.R & D].sub.ITIC] =
                 [[bar.R & D].sub.NITIC]            ITIC spend more
                                                    absolute dollars
                                                    on R&D than NITIC.
R&D intensity    [[bar.R&Dintensity].sub.ITIC] =
                 [[bar.R&Dintensity].sub.NITIC]     NITIC are more R&D
                                                    intensive than
                                                    ITIC.
ROA              [[bar.ROA].sub.ITIC] =
                 [[bar.ROA].sub.NITIC]              No statistical
                                                    difference
ROE              [[bar.ROE].sub.ITIC] =
                 [[bar.ROE].sub.ITIC]               No statistical
                                                    difference

Dataset          p-value

Assets            .000
Revenues          .000
R&D               .000
R&D intensity     .024
ROA               .550
ROE               .631

* ITIC refers to Information Technology Innovative Companies
NITIC refers to Companies that are not Innovators of Information
Technology

TABLE 3: POST IMPLEMENTATION YEARS: 2000, 2001 AND 2002

Dataset                Comparison of means            Conclusion *

Assets           [[bar.Assets].sub.ITIC] =
                 [[bar.Assets].sub.NITIC]           ITIC have more
                                                    assets than NITIC
Revenues         [[bar.Revenues].sub.ITIC] =
                 [[bar.Revenues].sub.NITIC]         ITIC have more
                                                    revenues than
                                                    NITIC.
R&D              [[bar.R & D].sub.ITIC] =
                 [[bar.R & D].sub.NITIC]            ITIC spend more
                                                    absolute dollars
                                                    on R&D than NITIC.
R&D intensity    [[bar.R&Dintensity].sub.ITIC] =
                 [[bar.R&Dintensity].sub.NITIC]     NITIC are more R&D
                                                    intensive than
                                                    ITIC.
ROA              [[bar.ROA].sub.ITIC] =
                 [[bar.ROA].sub.NITIC]              No statistical
                                                    difference
ROE              [[bar.ROE].sub.ITIC] =
                 [[bar.ROE].sub.ITIC]               No statistical
                                                    difference
Dataset          p-value

Assets            .000
Revenues          .000
R&D               .001
R&D intensity     .034
ROA               .246
ROE               .558

* ITIC refers to Information Technology Innovative Companies
NITIC refers to Companies that are not Innovators of Information
Technology

REFERENCES

Brockhoff, K., "Exploring Strategic R&D Success Factors", Technology Analysis & Strategic Management, Vol. 15(3), 2003, 333.

Brynjolfsson, E., "Beyond the Productivity Paradox", Communications of the ACM, Vol. 41, 1998, 49-55.

Brynjolfsson, E. and L. Hitt, "Beyond the Productivity Paradox", Communications of the ACM, Vol. 41, 1998, 49-55.

Chesbrough H., "A Better Way to Innovate", Harvard Business Review, Vol. 81(7), 2003, 12.

Christensen, C., "The Innovator's Dilemma", Harvard Business School Press, Boston, 1997.

CSC, "Critical Issues of Information Systems Management", 14th Annual Survey of I/S Management Issues, 2001.

Dranove, D., M. Peteraf and M. Shanley, "Do Strategic Groups Exist?: An Economic Framework for Analysis", Strategic Management Journal, Vol. 19, 1998, 1029-1044.

Guan, J. and N. Ma. "Innovative Capability and Export Performance of Chinese Firms", Technovation. Vol. 23(9); 2003, 737.

Hickman, C., and C. Raia, "Incubating Innovation", Journal of Business Strategy, 23, 2002, 14-18.

Hitt, L., and E. Brynjolfsson, "Productivity, Business Profitability, and Consumer Surplus: Three Different Measures of Information Technology Value", MIS Quarterly, Vol. 20, 1996, 121-142.

Hitt, L., D. Wu and X. Zhou, "ERP Investment and Productivity Measures", Journal of Management Information Systems, Vol. 19, 2002, 71-98.

Lee, J., "Innovation and Strategic Divergence: An Empirical Study of the U.S. Pharmaceutical Industry from 1920 to 1960", Management Science, Vol. 49(2), 2003. 143-159.

McKinsley and Company, "US Productivity Report: 1995-2000", 2002.

Peteraf, M., and D. Shanley, "Getting to Know You: A Theory of Strategic Group Identity", Strategic Management Journal, Vol. 18, 1997, 519-528.

Rai, A., R. Patnayakuni and N. Patnayakuni, "Technology Investment and Business Performance", Communications of the ACM, Vol. 40, 1997, 89-97.

Shervani, T. and P. C. Zerrillo, "The Albatross of Product Innovation", Business Horizons, January February, 1997, 57-62.

Shin, N., "The Impact of Information Technology on Financial Performance: The Importance of Strategic Choice", European Journal of Information Systems, Vol. 10, 2001, 227-236.

Stiroh, K., "Investing in Information Technology: Productivity Payoffs for U.S. Industries", Current Issues in Economics and Finance, Vol. 7, 2001, 1-6.

Author Profile

Dr. Gregory M. Kellar earned his Ph.D. at the University of Tennessee, Knoxville in 1996. Currently he is an assistant professor of business at Penn State University, Delaware County.

Dr. John Xiaoqun Zhang earned his Ph.D. at Pittsburgh University. Currently he is an assistant professor of management at Penn State University at Harrisburg.

Dr. Anthony M. Akel earned his Ph.D. at Northwestern University in 1974. Currently he is a professor of management at C.W. Post Campus, Long Island University.